skip to main content
10.1145/3085158acmconferencesBook PagePublication PageshpdcConference Proceedingsconference-collections
SEM4HPC '17: Proceedings of the 2017 Workshop on Software Engineering Methods for Parallel and High Performance Applications
ACM2017 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
HPDC '17: The 26th International Symposium on High-Performance Parallel and Distributed Computing Washington DC USA 26 June 2017
ISBN:
978-1-4503-5000-6
Published:
26 June 2017
Sponsors:
University of Arizona, SIGARCH
In-Cooperation:
Recommend ACM DL
ALREADY A SUBSCRIBER?SIGN IN

Reflects downloads up to 16 Feb 2025Bibliometrics
Skip Abstract Section
Abstract

It is our great pleasure to welcome you to the Workshop on Software Engineering Methods for Parallel and High Performance Applications -- SEM4HPC 2017.

The workshop aims to discuss parallel computing beyond traditional scientific computing and using them to develop enterprise and industrial applications. Compared to the traditional sequential computing paradigm, the software development, analysis and migration tools for parallel and high performance applications are far less matured for the IT industry to make a shift towards the new computing paradigm. The mission of this workshop is to bring the global industry and academic experts in this area to identify various research challenges that exist in software engineering methods for parallel and high performance application development, maintenance and migration. The workshop also aims to bring out the current state of the art and practice of the software engineering methods through case-studies, novel research ideas, and keynote and invited talks.

The call for papers attracted submissions from the Netherlands, India, and the United States. We received five technical papers out of which three were selected with an acceptance ratio of 60%.

We also encourage attendees to attend the keynote and invited talk presentations. These valuable and insightful talks can and will guide us to a better understanding of challenges in this area:

  • Keynote: "MPI Acceleration of Image Classification: Are We Seeing the Resurgence of MPI in Solving Big Data Problems?", Sameer Kumar (IBM Research, India)

  • Invited Talk: "READEX Tool Suite for Energy-efficiency Tuning of HPC Applications", Michael Gerndt (Technical University of Munich, Germany)

Skip Table Of Content Section
SESSION: Session 1
invited-talk
MPI Acceleration of Image Classification: Are We Seeing the Resurgence of MPI in Solving Big Data Problems?

Recent work has shown the effectiveness of the MPI programming paradigm in accelerating image classification via the Stochastic Gradient Descent optimization technique. Applications such as Caffe, Torch and Tensor Flow, that use Graphic Processing Unit ...

research-article
How Effective is Design Abstraction in Thrust?: An Empirical Evaluation

High performance computing applications are far more difficult to write, therefore, practitioners expect a well-tuned software to last long and provide optimized performance even when the hardware is upgraded. It may also be necessary to write software ...

SESSION: Session 2
keynote
READEX Tool Suite for Energy-efficiency Tuning of HPC Applications

The European Union Horizon 2020 READEX project is developing a tool suite for dynamic energy tuning of HPC applications. The tool suite performs an analysis during design-time before production run to construct a tuning model encapsulated with the best-...

research-article
PRESGen: A Fully Automatic Equivalence Checker for Validating Optimizing and Parallelizing Transformations

Petri net has been a popular choice of model of computation (MoC) for representing parallel programs. PRES+ is an extension of the traditional Petri net model which is specially equipped to precisely model embedded systems. Since multi-core and ...

research-article
Using High Level GPU Tasks to Explore Memory and Communications Options on Heterogeneous Platforms

Heterogeneous computing platforms that use GPUs for acceleration are becoming prevalent. Developing parallel applications for GPU platforms and optimizing GPU related applications for good performance is important. In this work, we develop a set of ...

Contributors
  • IBM Research
  • Birla Institute of Technology and Science, Pilani
  • Technical University of Munich
Index terms have been assigned to the content through auto-classification.

Recommendations

Acceptance Rates

SEM4HPC '17 Paper Acceptance Rate 3 of 5 submissions, 60%;
Overall Acceptance Rate 8 of 16 submissions, 50%
YearSubmittedAcceptedRate
SEM4HPC '175360%
SEM4HPC '1611545%
Overall16850%